A radar is a complex system that may actively transmit an electromagnetic waveform in the air and that may receive returns from echoes of this waveform modified by the environment. The returns can differ from the transmitted wave in terms of amplitude and phase shift: the reception scheme aims at extracting from these differences useful information on relevant objects in the environment usually called targets. The transmitted waveform and the antenna pattern are usually designed such as to allow extraction of specific and precise details. These serve a common objective for radar applications, which is to discern the targets from the environment or clutter, thermal noise and undesired signals such as jammers.
The useful information in a radar application is described from parameters such as range, angular position (azimuth/elevation) or Doppler frequency. These are used to distinguish a target from the environment and from unwanted signals. These are also used to distinguish between multiple targets in a scene; a spatial distribution of reflectors. The characteristics of the waveform and of the antenna pattern, such as bandwidth, observation time or beamwidth of the aperture illumination, determine the minimum separation, usually called resolution, between two returns from separate point sources in order for them to be distinguishable in each dimension (range, Doppler, and angular). Once returns are separated, they are attributed to one or multiple targets, or to clutter, or to jammers. Extended work has been done in the past for improvement of techniques to allow resolution between echoes.
In an attempt to allow for resolution between echoes in the azimuth dimension, standard techniques used are interpolation techniques. Separation of different object echoes is achieved by means of interpolating several discrete samples of processed returns, usually <<called hits>>, from a same object to locate the exact peak, corresponding to a good estimate of the true azimuth of the object. This peak can then be separated from another peak due to another object if a dip is present between the two peaks. Other techniques applied to extract the azimuth position of the object are beamforming and target/sidelobe subtraction. Beamforming is applied when antenna arrays are considered: different elements of the array can be combined accordingly to synthesize a spatial filter that allows, by virtue of a proper processing, separating two returns from different azimuth angles. Particular beamforming techniques include null steering that enable placing a notch at the azimuth angles where undesired returns arrive. Algorithms such as MUSIC (<<MUltiple Signal Classification>>) and Capon are applied in beamforming schemes to separate different closely spaced sources. Direction of arrival algorithms aim to derive from multiple receiver elements the location of an object generating the echo by means of deriving the phase difference between the echoes, at each element. Subtraction techniques are several methods that allow lowering or canceling sidelobes of the antenna pattern in order to be able to locate an object return even when closely positioned by a stronger one. Among these methods are the CLEAN techniques, applied either as beam-removing techniques or in the filtering as image-residue approach on the Doppler-delay plane, to subtract strong echoes from a combined return of multiple echoes superimposed in order to unmask weaker echoes. For the azimuth dimension, CLEAN techniques are applied using model matching maximum likelihood techniques. These apply stronger target cancellation to uncover weaker targets, by using an image-residue approach on the Doppler-delay plane. Unfortunately, drawbacks of the CLEAN algorithm are, among others, the need for a complete knowledge of the transmitted signal, the fact that it is a non linear procedure due to threshold procedure in following iterations, a hypothesis of deterministic sidelobe pattern, artifacts due to constructive/destructive interference due to contiguous targets or spacing closer than a resolution cell, hypothesis required on number of targets expected, a combinatorial approach and computational expense if many extended targets are present. It is an aim of the present invention to overcome at least some of these drawbacks.
In an attempt to allow for resolution between echoes in the range dimension, the standard technique used is CFAR (<<Constant False Alarm Rate>>) and pulse compression. This last technique is essentially applying a matched filter at reception when the transmitted signal is modulated in frequency or phase to obtain a large bandwidth. The sidelobe level of the output of the matched filter depends on the transmitted waveform. Sidelobe suppression techniques have been developed by designing coding schemes that generate low sidelobes, these are called spectral weighting or windowing. Other techniques are related to mismatched filtering as opposed to matched filtering. Mismatched filtering techniques can be based on different inverse filtering methods: some are based on weight selection for the filtering based on minimization of some sidelobe level parameter while others are based on least squares schemes or developed for particular coding schemes. Mismatched filtering techniques usually cause a widening and lowering of the mainlobe of the output of the filter, the latter named mismatch loss. Unknown distortion in the emitted signal raises these sidelobes. It is an aim of the present invention to overcome at least some of these drawbacks.
For the range dimension, Blunt and Gerlach developed the APC scheme (<<Adaptive Pulse Compression>>) as disclosed in the U.S. Pat. No. 7,106,250 and U.S. Pat. No. 7,298,315TBD respectively titled <<Robust Predictive Deconvolution Method and System>> and <<Radar Pulse Compression Repair>>. The APC scheme is an iterative method to generate a linear minimum mean square estimate filter given the received signal samples and the transmitted signal. It is an implementation of the Wiener filter for finite observation samples of the received signal. Unfortunately, a major drawback of the APC scheme proposed by Blunt and Gerlach is, among others, the need for a perfect knowledge of the output signal, while the actual output signal is bound to be distorted. Yet another drawback of the APC scheme is the need for a perfect target matching, the target having to be placed at the center of the range cell. Yet another drawback of the APC scheme is that the Doppler compensation algorithm depends on the waveform. Yet another drawback of the APC scheme is that the clutter and Doppler spread are not considered, hereby favoring target masking. It is an aim of the present invention to overcome at least some of these drawbacks.
A previous publication titled “Performance of Reiterated LMMSE Filtering and Coded Radar Waveforms” (Proceedings of the 5th European Radar Conference, Amsterdam, October 2008) discloses a method for filtering a radar signal after it has been reflected by a target. However, the method disclosed in this publication achieves only compensation for the sidelobes of the echoes of an unknown scene of multiple targets. The method disclosed fails at compensating for an unwanted and beforehand unknown distortion in the emitted signal.